AI Outline Writer - Added image generation and display for sections
This commit is contained in:
ajaysi
@@ -10,6 +10,7 @@ from typing import Dict, List, Optional
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from enum import Enum
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from dataclasses import dataclass
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from loguru import logger
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import json
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from lib.gpt_providers.text_generation.main_text_generation import llm_text_gen
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from lib.gpt_providers.text_to_image_generation.main_generate_image_from_prompt import generate_image
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@@ -84,216 +85,196 @@ class BlogOutlineGenerator:
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self.outline = {}
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self.section_contents = {}
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async def generate_outline(self, topic: str) -> Dict:
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"""Generate a comprehensive outline based on the topic and configuration."""
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def generate_outline(self, topic: str) -> Dict[str, List[str]]:
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"""Generate a blog outline based on the topic and configuration."""
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try:
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# Step 1: Generate main sections
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main_sections = await self._generate_main_sections(topic)
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# Create a focused prompt for outline generation
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prompt = f"""Generate a blog outline for topic: {topic}
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Content Type: {self.config.content_type.value}
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Target Audience: {self.config.target_audience}
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Content Depth: {self.config.content_depth.value}
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Style: {self.config.outline_style.value}
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Word Count Target: {self.config.target_word_count}
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Main Sections: {self.config.num_main_sections}
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Subsections per Section: {self.config.num_subsections_per_section}
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Requirements:
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- Create exactly {self.config.num_main_sections} main sections
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- Each section should have exactly {self.config.num_subsections_per_section} subsections
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- Focus on {self.config.content_type.value} content style
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- Target {self.config.target_audience} audience
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- Maintain {self.config.content_depth.value} depth
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- Follow {self.config.outline_style.value} style
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- Optimize for {self.config.target_word_count} words total
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IMPORTANT: You must return a valid JSON object with main sections as keys and lists of subsections as values.
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Example format: {{"Section 1": ["Subsection 1.1", "Subsection 1.2"], "Section 2": ["Subsection 2.1", "Subsection 2.2"]}}
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Do not include any additional text or explanations, only the JSON object."""
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# Get outline from LLM
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outline_json = llm_text_gen(prompt)
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# Step 2: Generate subsections for each main section
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detailed_sections = await self._generate_subsections(main_sections)
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# Clean the response to ensure it's valid JSON
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outline_json = outline_json.strip()
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if not outline_json.startswith('{'):
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outline_json = outline_json[outline_json.find('{'):]
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if not outline_json.endswith('}'):
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outline_json = outline_json[:outline_json.rfind('}')+1]
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# Step 3: Add introduction and conclusion if requested
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# Parse the outline
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try:
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outline = json.loads(outline_json)
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except json.JSONDecodeError as e:
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logger.error(f"JSON parsing error: {str(e)}")
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logger.error(f"Raw response: {outline_json}")
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# Fallback to a basic outline structure
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outline = {
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f"Section {i+1}": [f"Subsection {i+1}.{j+1}" for j in range(self.config.num_subsections_per_section)]
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for i in range(self.config.num_main_sections)
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}
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# Add introduction and conclusion if configured
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if self.config.include_introduction:
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detailed_sections["Introduction"] = await self._generate_introduction(topic)
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outline = {"Introduction": ["Overview", "Importance", "What to Expect"]} | outline
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if self.config.include_conclusion:
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detailed_sections["Conclusion"] = await self._generate_conclusion(topic)
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outline["Conclusion"] = ["Summary", "Key Takeaways", "Next Steps"]
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# Step 4: Add FAQs if requested
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# Add FAQs if configured
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if self.config.include_faqs:
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detailed_sections["FAQs"] = await self._generate_faqs(topic)
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# Step 5: Add resources if requested
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if self.config.include_resources:
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detailed_sections["Additional Resources"] = await self._generate_resources(topic)
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self.outline = detailed_sections
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# Step 6: Generate content for each section
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await self._generate_section_contents(topic)
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return self.outline
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except Exception as err:
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logger.error(f"Failed to generate outline: {err}")
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raise
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async def _generate_main_sections(self, topic: str) -> List[str]:
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"""Generate main sections for the outline."""
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prompt = f"""Generate {self.config.num_main_sections} main sections for a {self.config.content_type.value}
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article about {topic} with the following characteristics:
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Content Type: {self.config.content_type.value}
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Content Depth: {self.config.content_depth.value}
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Target Word Count: {self.config.target_word_count}
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Target Audience: {self.config.target_audience}
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Style: {self.config.outline_style.value}
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Additional Requirements:
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- Each section should contribute to the overall word count goal
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- Sections should flow logically
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- Include key concepts and important points
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- Consider SEO optimization
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- Keywords to include: {', '.join(self.config.keywords or [])}
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- Topics to exclude: {', '.join(self.config.exclude_topics or [])}
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Please provide only the section titles, one per line."""
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response = await llm_text_gen(prompt)
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return [section.strip() for section in response.split('\n') if section.strip()]
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async def _generate_subsections(self, main_sections: List[str]) -> Dict[str, List[str]]:
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"""Generate subsections for each main section."""
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detailed_sections = {}
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for section in main_sections:
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prompt = f"""Generate {self.config.num_subsections_per_section} subsections for the following section:
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{section}
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Content Type: {self.config.content_type.value}
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Content Depth: {self.config.content_depth.value}
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Style: {self.config.outline_style.value}
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Each subsection should:
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- Be specific and focused
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- Support the main section's topic
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- Include key points to cover
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- Consider SEO optimization
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Please provide only the subsection titles, one per line."""
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response = await llm_text_gen(prompt)
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detailed_sections[section] = [sub.strip() for sub in response.split('\n') if sub.strip()]
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return detailed_sections
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async def _generate_introduction(self, topic: str) -> List[str]:
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"""Generate introduction subsections."""
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prompt = f"""Generate introduction subsections for an article about {topic}.
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Content Type: {self.config.content_type.value}
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Content Depth: {self.config.content_depth.value}
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Style: {self.config.outline_style.value}
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The introduction should:
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- Hook the reader
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- Present the main topic
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- Outline what's to come
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- Set the tone for the article
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Please provide only the subsection titles, one per line."""
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response = await llm_text_gen(prompt)
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return [sub.strip() for sub in response.split('\n') if sub.strip()]
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async def _generate_conclusion(self, topic: str) -> List[str]:
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"""Generate conclusion subsections."""
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prompt = f"""Generate conclusion subsections for an article about {topic}.
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Content Type: {self.config.content_type.value}
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Content Depth: {self.config.content_depth.value}
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Style: {self.config.outline_style.value}
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The conclusion should:
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- Summarize key points
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- Provide final thoughts
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- Include a call to action
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- Leave a lasting impression
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Please provide only the subsection titles, one per line."""
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response = await llm_text_gen(prompt)
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return [sub.strip() for sub in response.split('\n') if sub.strip()]
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async def _generate_faqs(self, topic: str) -> List[str]:
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"""Generate FAQ subsections."""
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prompt = f"""Generate FAQ subsections for an article about {topic}.
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Content Type: {self.config.content_type.value}
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Content Depth: {self.config.content_depth.value}
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Style: {self.config.outline_style.value}
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The FAQs should:
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- Address common questions
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- Cover important aspects
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- Be relevant to the target audience
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- Include both basic and advanced questions
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Please provide only the FAQ questions, one per line."""
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response = await llm_text_gen(prompt)
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return [sub.strip() for sub in response.split('\n') if sub.strip()]
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async def _generate_resources(self, topic: str) -> List[str]:
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"""Generate resource subsections."""
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prompt = f"""Generate resource subsections for an article about {topic}.
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Content Type: {self.config.content_type.value}
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Content Depth: {self.config.content_depth.value}
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Style: {self.config.outline_style.value}
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The resources should:
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- Include relevant links
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- Suggest further reading
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- Provide tools or references
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- Include related materials
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Please provide only the resource categories, one per line."""
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response = await llm_text_gen(prompt)
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return [sub.strip() for sub in response.split('\n') if sub.strip()]
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async def _generate_section_contents(self, topic: str):
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"""Generate content and images for each section."""
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for section, subsections in self.outline.items():
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if section not in ["Introduction", "Conclusion", "FAQs", "Additional Resources"]:
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# Generate content for the main section
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content_prompt = f"""Write a detailed section for a blog post about {topic}.
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Section Title: {section}
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Content Type: {self.config.content_type.value}
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Content Depth: {self.config.content_depth.value}
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Style: {self.config.outline_style.value}
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Target Word Count: {self.config.target_word_count // self.config.num_main_sections}
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Include:
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- Clear explanation of the main points
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- Examples and illustrations
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- Key takeaways
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- Relevant data or statistics
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"""
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content = await llm_text_gen(content_prompt)
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# Generate image prompt if images are enabled
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image_prompt = None
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image_path = None
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if self.config.include_images:
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image_prompt = f"""Create a detailed image prompt for a blog section about {topic}.
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Section: {section}
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Content: {content[:200]}...
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Style: {self.config.image_style}
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"""
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# Generate topic-specific FAQs
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faq_prompt = f"""Generate 3 specific and relevant FAQ questions for a blog post about: {topic}
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Content Type: {self.config.content_type.value}
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Target Audience: {self.config.target_audience}
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Content Depth: {self.config.content_depth.value}
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Requirements:
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- Questions should be specific to the topic
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- Cover common concerns and important aspects
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- Be relevant to the target audience
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- Include both basic and advanced questions
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Format: Return only a JSON array of 3 questions.
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Example format: ["Question 1?", "Question 2?", "Question 3?"]"""
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try:
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faq_json = llm_text_gen(faq_prompt)
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faq_json = faq_json.strip()
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if not faq_json.startswith('['):
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faq_json = faq_json[faq_json.find('['):]
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if not faq_json.endswith(']'):
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faq_json = faq_json[:faq_json.rfind(']')+1]
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image_prompt = await llm_text_gen(image_prompt)
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try:
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image_path = generate_image(
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image_prompt,
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title=section,
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description=content[:100],
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tags=self.config.keywords
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)
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except Exception as err:
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logger.warning(f"Failed to generate image for section {section}: {err}")
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self.section_contents[section] = SectionContent(
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title=section,
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content=content,
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image_prompt=image_prompt,
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image_path=image_path
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)
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faqs = json.loads(faq_json)
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outline["Frequently Asked Questions"] = faqs
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except Exception as e:
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logger.error(f"Error generating FAQs: {str(e)}")
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outline["Frequently Asked Questions"] = [
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f"Common Question about {topic} 1",
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f"Common Question about {topic} 2",
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f"Common Question about {topic} 3"
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]
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# Add resources if configured
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if self.config.include_resources:
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outline["Additional Resources"] = [
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"Further Reading",
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"Tools and References",
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"Related Topics"
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]
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return outline
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except Exception as e:
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logger.error(f"Error generating outline: {str(e)}")
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return {}
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def generate_section_content(self, section: str, subsections: List[str]) -> Optional[SectionContent]:
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"""Generate content for a section."""
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try:
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# Create a focused prompt for content generation
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prompt = f"""Generate content for section: {section}
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Subsections: {', '.join(subsections)}
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Content Type: {self.config.content_type.value}
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Target Audience: {self.config.target_audience}
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Content Depth: {self.config.content_depth.value}
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Style: {self.config.outline_style.value}
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Word Count Target: {self.config.target_word_count // self.config.num_main_sections}
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Requirements:
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- Write content for each subsection
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- Maintain {self.config.content_depth.value} depth
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- Target {self.config.target_audience} audience
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- Follow {self.config.outline_style.value} style
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- Optimize for {self.config.target_word_count // self.config.num_main_sections} words
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- Include relevant examples and data points
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- Use clear, engaging language
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Format: Return only a JSON object with 'content' and 'image_prompt' fields.
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Example format: {{"content": "Section content here...", "image_prompt": "Image description here..."}}"""
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# Get content from LLM
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content_json = llm_text_gen(prompt)
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content_data = json.loads(content_json)
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# Generate image if configured
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image_path = None
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if self.config.include_images:
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image_path = self.generate_section_image(section)
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return SectionContent(
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title=section,
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content=content_data["content"],
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image_prompt=content_data.get("image_prompt"),
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image_path=image_path
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)
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except Exception as e:
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logger.error(f"Error generating content for section {section}: {str(e)}")
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return None
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def generate_section_image(self, section: str) -> Optional[str]:
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"""Generate an image for a section."""
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try:
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# Create a focused prompt for image generation
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prompt = f"""Generate an image prompt for section: {section}
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Style: {self.config.image_style}
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Engine: {self.config.image_engine}
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Content Type: {self.config.content_type.value}
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Target Audience: {self.config.target_audience}
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Requirements:
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- Create a {self.config.image_style} style image
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- Optimize for {self.config.image_engine} engine
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- Match {self.config.content_type.value} content type
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- Appeal to {self.config.target_audience} audience
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- Be visually engaging and relevant
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Format: Return only a JSON object with an 'image_prompt' field.
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Example format: {{"image_prompt": "Detailed image description here..."}}"""
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# Get image prompt from LLM
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prompt_json = llm_text_gen(prompt)
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prompt_data = json.loads(prompt_json)
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# Generate image using the specified engine
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if self.config.image_engine == "Gemini-AI":
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image_path = generate_gemini_image(prompt_data["image_prompt"])
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elif self.config.image_engine == "Dalle3":
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image_path = generate_dalle_image(prompt_data["image_prompt"])
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else: # Stability-AI
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image_path = generate_stability_image(prompt_data["image_prompt"])
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return image_path
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except Exception as e:
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logger.error(f"Error generating image for section {section}: {str(e)}")
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return None
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def to_markdown(self) -> str:
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"""Convert outline to markdown format with content and images."""
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markdown = f"# {self.outline.get('Introduction', [''])[0]}\n\n"
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@@ -34,42 +34,126 @@ st.markdown("""
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border-radius: 4px;
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border: none;
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font-weight: bold;
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width: 100%;
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}
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.stButton>button:hover {
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background-color: #45a049;
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}
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/* Add specific styling for the generate outline button */
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.generate-outline-button {
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width: 100%;
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margin: 20px 0;
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}
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.generate-outline-button > button {
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width: 100%;
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height: 50px;
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font-size: 1.2rem;
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}
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.section-card {
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background-color: white;
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padding: 20px;
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border-radius: 8px;
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box-shadow: 0 2px 4px rgba(0,0,0,0.1);
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margin-bottom: 20px;
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width: 100%;
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}
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.content-preview {
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background-color: #f8f9fa;
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padding: 15px;
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border-radius: 4px;
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margin: 10px 0;
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width: 100%;
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}
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.image-container {
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display: flex;
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justify-content: center;
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margin: 20px 0;
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width: 100%;
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}
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.stats-card {
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background-color: #e8f5e9;
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padding: 15px;
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border-radius: 8px;
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margin: 10px 0;
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width: 100%;
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}
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.edit-section {
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background-color: #e3f2fd;
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padding: 15px;
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border-radius: 4px;
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margin: 10px 0;
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width: 100%;
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}
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.subsection-list {
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margin-left: 20px;
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width: 100%;
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}
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/* Main container width */
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.main .block-container {
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max-width: 100%;
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padding: 2rem;
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}
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/* Full width for the outline display */
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.outline-container {
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||||
width: 100%;
|
||||
max-width: 100%;
|
||||
margin: 0 auto;
|
||||
padding: 20px;
|
||||
}
|
||||
/* Section styling */
|
||||
.section-header {
|
||||
font-size: 1.5rem;
|
||||
font-weight: bold;
|
||||
color: #2c3e50;
|
||||
margin-bottom: 1rem;
|
||||
padding-bottom: 0.5rem;
|
||||
border-bottom: 2px solid #e0e0e0;
|
||||
}
|
||||
.subsection-item {
|
||||
font-size: 1.1rem;
|
||||
color: #34495e;
|
||||
margin: 0.5rem 0;
|
||||
padding-left: 1rem;
|
||||
}
|
||||
/* Content area styling */
|
||||
.content-area {
|
||||
background-color: white;
|
||||
padding: 2rem;
|
||||
border-radius: 8px;
|
||||
box-shadow: 0 2px 4px rgba(0,0,0,0.1);
|
||||
margin: 1rem 0;
|
||||
}
|
||||
/* Make sure all Streamlit elements use full width */
|
||||
.stMarkdown, .stText, .stTextArea, .stSelectbox, .stSlider {
|
||||
width: 100% !important;
|
||||
}
|
||||
/* Full width for code blocks */
|
||||
.stCodeBlock {
|
||||
width: 100% !important;
|
||||
}
|
||||
/* Full width for the main content */
|
||||
.main .block-container {
|
||||
padding-left: 2rem;
|
||||
padding-right: 2rem;
|
||||
max-width: 100%;
|
||||
}
|
||||
/* Adjust the main content area */
|
||||
.main .block-container > div {
|
||||
max-width: 100%;
|
||||
}
|
||||
/* Make sure the outline content uses full width */
|
||||
.outline-content {
|
||||
width: 100%;
|
||||
max-width: 100%;
|
||||
margin: 0;
|
||||
padding: 0;
|
||||
}
|
||||
/* Adjust the preview section */
|
||||
.preview-section {
|
||||
width: 100%;
|
||||
max-width: 100%;
|
||||
margin: 0;
|
||||
padding: 1rem;
|
||||
}
|
||||
</style>
|
||||
""", unsafe_allow_html=True)
|
||||
@@ -205,7 +289,7 @@ def display_section(section: str, subsections: List[str], content: Optional[Dict
|
||||
"""Display a section with its content and subsections."""
|
||||
st.markdown(f"""
|
||||
<div class="section-card">
|
||||
<h2>{section}</h2>
|
||||
<div class="section-header">{section}</div>
|
||||
""", unsafe_allow_html=True)
|
||||
|
||||
# Section editing controls
|
||||
@@ -225,37 +309,78 @@ def display_section(section: str, subsections: List[str], content: Optional[Dict
|
||||
</div>
|
||||
""", unsafe_allow_html=True)
|
||||
|
||||
# Display image if available
|
||||
if content.image_path:
|
||||
st.markdown('<div class="image-container">', unsafe_allow_html=True)
|
||||
st.image(content.image_path, caption=section, use_column_width=True)
|
||||
st.markdown('</div>', unsafe_allow_html=True)
|
||||
# Image generation and display - Always show if images are enabled
|
||||
if generator and generator.config.include_images:
|
||||
st.markdown("### Image Generation")
|
||||
col1, col2, col3 = st.columns([2, 2, 1])
|
||||
|
||||
# Display image prompt in expander
|
||||
if content.image_prompt:
|
||||
with st.expander("View Image Prompt"):
|
||||
st.code(content.image_prompt, language="text")
|
||||
with col1:
|
||||
image_style = st.selectbox(
|
||||
"Image Style",
|
||||
["realistic", "illustration", "minimalist", "photographic", "artistic"],
|
||||
index=["realistic", "illustration", "minimalist", "photographic", "artistic"].index(generator.config.image_style),
|
||||
key=f"img_style_{section}"
|
||||
)
|
||||
|
||||
with col2:
|
||||
image_engine = st.selectbox(
|
||||
"Image Engine",
|
||||
["Gemini-AI", "Dalle3", "Stability-AI"],
|
||||
index=["Gemini-AI", "Dalle3", "Stability-AI"].index(generator.config.image_engine),
|
||||
key=f"img_engine_{section}"
|
||||
)
|
||||
|
||||
with col3:
|
||||
if st.button("Generate Image", key=f"gen_img_{section}"):
|
||||
with st.spinner(f"Generating image for {section}..."):
|
||||
# Update config with selected options
|
||||
generator.config.image_style = image_style
|
||||
generator.config.image_engine = image_engine
|
||||
image_path = generator.generate_section_image(section)
|
||||
if image_path:
|
||||
st.success("Image generated successfully!")
|
||||
st.experimental_rerun()
|
||||
else:
|
||||
st.error("Failed to generate image")
|
||||
|
||||
# Display existing image if available
|
||||
if content.image_path:
|
||||
st.markdown('<div class="image-container">', unsafe_allow_html=True)
|
||||
st.image(content.image_path, caption=section, use_column_width=True)
|
||||
st.markdown('</div>', unsafe_allow_html=True)
|
||||
|
||||
# Display image prompt in expander
|
||||
if content.image_prompt:
|
||||
with st.expander("View Image Prompt"):
|
||||
st.code(content.image_prompt, language="text")
|
||||
|
||||
# Edit mode controls
|
||||
if edit_mode:
|
||||
st.markdown("### Edit Content")
|
||||
# Edit content
|
||||
edited_content = edit_section_content(section, content.content)
|
||||
content.content = edited_content
|
||||
if edited_content != content.content:
|
||||
content.content = edited_content
|
||||
st.experimental_rerun()
|
||||
|
||||
st.markdown("### Edit Subsections")
|
||||
# Edit subsections
|
||||
edited_subsections = edit_subsections(section, subsections)
|
||||
subsections[:] = edited_subsections
|
||||
if edited_subsections != subsections:
|
||||
subsections[:] = edited_subsections
|
||||
st.experimental_rerun()
|
||||
|
||||
st.markdown("### Edit Metadata")
|
||||
# Edit metadata
|
||||
if generator:
|
||||
edit_section_metadata(section, generator)
|
||||
|
||||
# Display subsections
|
||||
st.markdown("### Subsections")
|
||||
st.markdown('<div class="subsection-list">', unsafe_allow_html=True)
|
||||
for subsection in subsections:
|
||||
st.markdown(f"- {subsection}")
|
||||
st.markdown('</div>', unsafe_allow_html=True)
|
||||
else:
|
||||
# Display subsections in view mode
|
||||
st.markdown("### Subsections")
|
||||
st.markdown('<div class="subsection-list">', unsafe_allow_html=True)
|
||||
for subsection in subsections:
|
||||
st.markdown(f'<div class="subsection-item">• {subsection}</div>', unsafe_allow_html=True)
|
||||
st.markdown('</div>', unsafe_allow_html=True)
|
||||
|
||||
st.markdown("</div>", unsafe_allow_html=True)
|
||||
|
||||
@@ -297,13 +422,6 @@ def display_stats(generator, outline):
|
||||
""", unsafe_allow_html=True)
|
||||
|
||||
def main():
|
||||
st.set_page_config(
|
||||
page_title="Blog Outline Generator",
|
||||
page_icon="📝",
|
||||
layout="wide",
|
||||
initial_sidebar_state="expanded"
|
||||
)
|
||||
|
||||
# Header with description
|
||||
st.title("Blog Outline Generator")
|
||||
st.markdown("""
|
||||
@@ -311,179 +429,311 @@ def main():
|
||||
Customize your outline with various options and get detailed content for each section.
|
||||
""")
|
||||
|
||||
# Sidebar for configuration
|
||||
with st.sidebar:
|
||||
st.header("Configuration")
|
||||
# Main content area with full width
|
||||
st.markdown('<div class="outline-container">', unsafe_allow_html=True)
|
||||
|
||||
# Move topic input to main area and make it more prominent
|
||||
st.markdown("### Enter Your Blog Topic")
|
||||
topic = st.text_input("", placeholder="Enter your blog topic here for creating outline...", key="blog_topic")
|
||||
|
||||
st.markdown("---") # Add a separator
|
||||
st.markdown("### Configuration Options")
|
||||
|
||||
# Create tabs for different configuration sections
|
||||
tab1, tab2, tab3, tab4 = st.tabs([
|
||||
"📝 Content Type & Target",
|
||||
"📊 Content Structure",
|
||||
"🎨 Style & Sections",
|
||||
"🖼️ Image & Optimization"
|
||||
])
|
||||
|
||||
with tab1:
|
||||
st.markdown("#### Content Type & Target")
|
||||
col1, col2, col3 = st.columns(3)
|
||||
|
||||
# Basic settings
|
||||
topic = st.text_input("Blog Topic", placeholder="Enter your blog topic")
|
||||
content_type = st.selectbox(
|
||||
"Content Type",
|
||||
[type.value for type in ContentType]
|
||||
)
|
||||
content_depth = st.selectbox(
|
||||
"Content Depth",
|
||||
[depth.value for depth in ContentDepth]
|
||||
)
|
||||
outline_style = st.selectbox(
|
||||
"Outline Style",
|
||||
[style.value for style in OutlineStyle]
|
||||
)
|
||||
with col1:
|
||||
content_type = st.selectbox(
|
||||
"Content Type",
|
||||
[type.value for type in ContentType],
|
||||
index=[type.value for type in ContentType].index(ContentType.GUIDE.value),
|
||||
help="Select the type of content you want to generate"
|
||||
)
|
||||
|
||||
# Content structure
|
||||
st.subheader("Content Structure")
|
||||
target_word_count = st.slider("Target Word Count", 500, 5000, 2000, 100)
|
||||
num_main_sections = st.slider("Number of Main Sections", 3, 10, 5)
|
||||
num_subsections = st.slider("Subsections per Section", 2, 5, 3)
|
||||
with col2:
|
||||
target_audience = st.selectbox(
|
||||
"Target Audience",
|
||||
["General", "Technical", "Professional", "Academic", "Business", "Students", "Developers"],
|
||||
index=0,
|
||||
help="Select your target audience"
|
||||
)
|
||||
|
||||
# Advanced settings
|
||||
with st.expander("Advanced Settings"):
|
||||
include_intro = st.checkbox("Include Introduction", value=True)
|
||||
include_conclusion = st.checkbox("Include Conclusion", value=True)
|
||||
include_faqs = st.checkbox("Include FAQs", value=True)
|
||||
include_resources = st.checkbox("Include Resources", value=True)
|
||||
with col3:
|
||||
language = st.selectbox(
|
||||
"Language",
|
||||
["English", "Spanish", "French", "German", "Italian", "Portuguese", "Chinese", "Japanese", "Korean"],
|
||||
index=0,
|
||||
help="Select the language for your content"
|
||||
)
|
||||
|
||||
with tab2:
|
||||
st.markdown("#### Content Structure")
|
||||
col1, col2 = st.columns(2)
|
||||
|
||||
with col1:
|
||||
num_main_sections = st.slider(
|
||||
"Number of Main Sections",
|
||||
min_value=3,
|
||||
max_value=10,
|
||||
value=5,
|
||||
step=1,
|
||||
help="Choose how many main sections your outline should have"
|
||||
)
|
||||
|
||||
num_subsections = st.slider(
|
||||
"Subsections per Section",
|
||||
min_value=2,
|
||||
max_value=5,
|
||||
value=3,
|
||||
step=1,
|
||||
help="Choose how many subsections each main section should have"
|
||||
)
|
||||
|
||||
with col2:
|
||||
target_word_count = st.slider(
|
||||
"Target Word Count",
|
||||
min_value=500,
|
||||
max_value=5000,
|
||||
value=2000,
|
||||
step=100,
|
||||
help="Set your target word count for the entire blog post"
|
||||
)
|
||||
|
||||
# Display content statistics
|
||||
st.markdown("##### Content Statistics")
|
||||
st.markdown(f"""
|
||||
- Estimated Sections: {num_main_sections}
|
||||
- Total Subsections: {num_main_sections * num_subsections}
|
||||
- Target Word Count: {target_word_count}
|
||||
- Average Words per Section: {target_word_count // num_main_sections}
|
||||
""")
|
||||
|
||||
with tab3:
|
||||
st.markdown("#### Style & Sections")
|
||||
col1, col2 = st.columns(2)
|
||||
|
||||
with col1:
|
||||
content_depth = st.selectbox(
|
||||
"Content Depth",
|
||||
[depth.value for depth in ContentDepth],
|
||||
index=[depth.value for depth in ContentDepth].index(ContentDepth.INTERMEDIATE.value),
|
||||
help="Select the depth of content coverage"
|
||||
)
|
||||
|
||||
outline_style = st.selectbox(
|
||||
"Outline Style",
|
||||
[style.value for style in OutlineStyle],
|
||||
index=[style.value for style in OutlineStyle].index(OutlineStyle.MODERN.value),
|
||||
help="Select the style of your outline"
|
||||
)
|
||||
|
||||
with col2:
|
||||
st.markdown("##### Additional Sections")
|
||||
include_intro = st.checkbox("Include Introduction", value=True, help="Add an introduction section")
|
||||
include_conclusion = st.checkbox("Include Conclusion", value=True, help="Add a conclusion section")
|
||||
include_faqs = st.checkbox("Include FAQs", value=True, help="Add a FAQ section")
|
||||
include_resources = st.checkbox("Include Resources", value=True, help="Add a resources section")
|
||||
|
||||
with tab4:
|
||||
st.markdown("#### Image & Optimization")
|
||||
col1, col2 = st.columns(2)
|
||||
|
||||
with col1:
|
||||
st.markdown("##### Image Settings")
|
||||
include_images = st.checkbox("Enable Image Generation", value=True, help="Enable AI image generation for sections")
|
||||
|
||||
# Image settings
|
||||
st.subheader("Image Settings")
|
||||
include_images = st.checkbox("Include Images", value=True)
|
||||
if include_images:
|
||||
image_style = st.selectbox(
|
||||
"Image Style",
|
||||
["realistic", "illustration", "minimalist", "photographic", "artistic"]
|
||||
["realistic", "illustration", "minimalist", "photographic", "artistic"],
|
||||
index=0,
|
||||
help="Select the style for generated images"
|
||||
)
|
||||
|
||||
image_engine = st.selectbox(
|
||||
"Image Engine",
|
||||
["Gemini-AI", "Dalle3", "Stability-AI"]
|
||||
["Gemini-AI", "Dalle3", "Stability-AI"],
|
||||
index=0,
|
||||
help="Select the AI engine for image generation"
|
||||
)
|
||||
|
||||
with col2:
|
||||
st.markdown("##### Content Optimization")
|
||||
keywords = st.text_area(
|
||||
"Keywords (comma-separated)",
|
||||
help="Enter keywords for SEO optimization, separated by commas"
|
||||
)
|
||||
|
||||
# Target audience and language
|
||||
st.subheader("Target Audience")
|
||||
target_audience = st.text_input("Target Audience", value="general")
|
||||
language = st.text_input("Language", value="English")
|
||||
|
||||
# Keywords and exclusions
|
||||
st.subheader("Content Optimization")
|
||||
keywords = st.text_area("Keywords (comma-separated)")
|
||||
exclude_topics = st.text_area("Topics to Exclude (comma-separated)")
|
||||
exclude_topics = st.text_area(
|
||||
"Topics to Exclude (comma-separated)",
|
||||
help="Enter topics you want to exclude from the content"
|
||||
)
|
||||
|
||||
# Main content area
|
||||
if topic:
|
||||
# Create configuration
|
||||
config = OutlineConfig(
|
||||
content_type=ContentType(content_type),
|
||||
content_depth=ContentDepth(content_depth),
|
||||
outline_style=OutlineStyle(outline_style),
|
||||
target_word_count=target_word_count,
|
||||
num_main_sections=num_main_sections,
|
||||
num_subsections_per_section=num_subsections,
|
||||
include_introduction=include_intro,
|
||||
include_conclusion=include_conclusion,
|
||||
include_faqs=include_faqs,
|
||||
include_resources=include_resources,
|
||||
include_images=include_images,
|
||||
image_style=image_style if include_images else "realistic",
|
||||
image_engine=image_engine if include_images else "Gemini-AI",
|
||||
target_audience=target_audience,
|
||||
language=language,
|
||||
keywords=[k.strip() for k in keywords.split(',')] if keywords else None,
|
||||
exclude_topics=[t.strip() for t in exclude_topics.split(',')] if exclude_topics else None
|
||||
)
|
||||
|
||||
# Initialize generator
|
||||
generator = BlogOutlineGenerator(config)
|
||||
|
||||
# Generate outline
|
||||
if st.button("Generate Outline"):
|
||||
with st.spinner("Generating outline and content..."):
|
||||
try:
|
||||
# Add progress bar
|
||||
progress_bar = st.progress(0)
|
||||
for i in range(100):
|
||||
time.sleep(0.01)
|
||||
progress_bar.progress(i + 1)
|
||||
|
||||
outline = asyncio.run(generator.generate_outline(topic))
|
||||
|
||||
# Display results
|
||||
st.success("Outline generated successfully!")
|
||||
|
||||
# Display statistics
|
||||
display_stats(generator, outline)
|
||||
|
||||
# Output format selection
|
||||
output_format = st.radio(
|
||||
"Output Format",
|
||||
["Preview", "Markdown", "JSON", "HTML"]
|
||||
)
|
||||
|
||||
if output_format == "Preview":
|
||||
# Display outline with content and images
|
||||
for section, subsections in outline.items():
|
||||
content = generator.section_contents.get(section)
|
||||
display_section(section, subsections, content)
|
||||
|
||||
elif output_format == "Markdown":
|
||||
st.code(generator.to_markdown(), language="markdown")
|
||||
st.download_button(
|
||||
"Download Markdown",
|
||||
generator.to_markdown(),
|
||||
file_name="blog_outline.md",
|
||||
mime="text/markdown"
|
||||
)
|
||||
|
||||
elif output_format == "JSON":
|
||||
json_output = json.dumps({
|
||||
"outline": outline,
|
||||
"contents": {
|
||||
section: {
|
||||
"title": content.title,
|
||||
"content": content.content,
|
||||
"image_prompt": content.image_prompt,
|
||||
"image_path": content.image_path
|
||||
}
|
||||
for section, content in generator.section_contents.items()
|
||||
}
|
||||
}, indent=2)
|
||||
st.code(json_output, language="json")
|
||||
st.download_button(
|
||||
"Download JSON",
|
||||
json_output,
|
||||
file_name="blog_outline.json",
|
||||
mime="application/json"
|
||||
)
|
||||
|
||||
elif output_format == "HTML":
|
||||
# Add HTML export functionality
|
||||
html_output = f"""
|
||||
<!DOCTYPE html>
|
||||
<html>
|
||||
<head>
|
||||
<title>{topic} - Blog Outline</title>
|
||||
<style>
|
||||
body {{ font-family: Arial, sans-serif; max-width: 800px; margin: 0 auto; padding: 20px; }}
|
||||
.section {{ margin-bottom: 30px; }}
|
||||
.content {{ background: #f8f9fa; padding: 15px; border-radius: 4px; }}
|
||||
img {{ max-width: 100%; height: auto; }}
|
||||
</style>
|
||||
</head>
|
||||
<body>
|
||||
<h1>{topic}</h1>
|
||||
{generator.to_markdown().replace('#', '##')}
|
||||
</body>
|
||||
</html>
|
||||
"""
|
||||
st.code(html_output, language="html")
|
||||
st.download_button(
|
||||
"Download HTML",
|
||||
html_output,
|
||||
file_name="blog_outline.html",
|
||||
mime="text/html"
|
||||
)
|
||||
st.markdown("---") # Add a separator before the generate button
|
||||
|
||||
# Create configuration
|
||||
config = OutlineConfig(
|
||||
content_type=ContentType(content_type),
|
||||
content_depth=ContentDepth(content_depth),
|
||||
outline_style=OutlineStyle(outline_style),
|
||||
target_word_count=target_word_count,
|
||||
num_main_sections=num_main_sections,
|
||||
num_subsections_per_section=num_subsections,
|
||||
include_introduction=include_intro,
|
||||
include_conclusion=include_conclusion,
|
||||
include_faqs=include_faqs,
|
||||
include_resources=include_resources,
|
||||
include_images=include_images,
|
||||
image_style=image_style if include_images else "realistic",
|
||||
image_engine=image_engine if include_images else "Gemini-AI",
|
||||
target_audience=target_audience,
|
||||
language=language,
|
||||
keywords=[k.strip() for k in keywords.split(',')] if keywords else None,
|
||||
exclude_topics=[t.strip() for t in exclude_topics.split(',')] if exclude_topics else None
|
||||
)
|
||||
|
||||
# Initialize generator
|
||||
generator = BlogOutlineGenerator(config)
|
||||
|
||||
# Store the generated outline in session state
|
||||
if 'outline' not in st.session_state:
|
||||
st.session_state.outline = None
|
||||
if 'section_contents' not in st.session_state:
|
||||
st.session_state.section_contents = {}
|
||||
|
||||
# Generate outline button with full width
|
||||
st.markdown('<div class="generate-outline-button">', unsafe_allow_html=True)
|
||||
if not topic:
|
||||
st.warning("Please enter a blog topic to generate the outline.")
|
||||
if st.button("Generate Outline", type="primary", use_container_width=True, disabled=not topic):
|
||||
with st.spinner("Generating outline and content..."):
|
||||
try:
|
||||
# Add progress bar
|
||||
progress_bar = st.progress(0)
|
||||
for i in range(100):
|
||||
time.sleep(0.01)
|
||||
progress_bar.progress(i + 1)
|
||||
|
||||
except Exception as e:
|
||||
st.error(f"Error generating outline: {str(e)}")
|
||||
else:
|
||||
st.info("Please enter a blog topic to get started.")
|
||||
outline = generator.generate_outline(topic)
|
||||
st.session_state.outline = outline
|
||||
st.session_state.section_contents = generator.section_contents
|
||||
|
||||
# Display results
|
||||
st.success("Outline generated successfully!")
|
||||
|
||||
# Add copy button and display outline in full width
|
||||
st.markdown('<div class="outline-content">', unsafe_allow_html=True)
|
||||
outline_text = json.dumps(outline, indent=2)
|
||||
st.code(outline_text, language="json")
|
||||
st.button("Copy Outline", key="copy_outline",
|
||||
help="Copy the outline to clipboard",
|
||||
on_click=lambda: st.write(f'<script>navigator.clipboard.writeText(`{outline_text}`)</script>',
|
||||
unsafe_allow_html=True))
|
||||
st.markdown('</div>', unsafe_allow_html=True)
|
||||
|
||||
# Display statistics
|
||||
display_stats(generator, outline)
|
||||
|
||||
# Output format selection
|
||||
output_format = st.radio(
|
||||
"Output Format",
|
||||
["Preview", "Markdown", "JSON", "HTML"]
|
||||
)
|
||||
|
||||
if output_format == "Preview":
|
||||
# Display outline with content and images
|
||||
st.markdown('<div class="preview-section">', unsafe_allow_html=True)
|
||||
for section, subsections in outline.items():
|
||||
content = generator.section_contents.get(section)
|
||||
display_section(section, subsections, content, generator)
|
||||
st.markdown('</div>', unsafe_allow_html=True)
|
||||
|
||||
elif output_format == "Markdown":
|
||||
markdown_output = generator.to_markdown()
|
||||
st.markdown('<div class="outline-content">', unsafe_allow_html=True)
|
||||
st.code(markdown_output, language="markdown")
|
||||
st.download_button(
|
||||
"Download Markdown",
|
||||
markdown_output,
|
||||
file_name="blog_outline.md",
|
||||
mime="text/markdown"
|
||||
)
|
||||
st.markdown('</div>', unsafe_allow_html=True)
|
||||
|
||||
elif output_format == "JSON":
|
||||
json_output = json.dumps({
|
||||
"outline": outline,
|
||||
"contents": {
|
||||
section: {
|
||||
"title": content.title,
|
||||
"content": content.content,
|
||||
"image_prompt": content.image_prompt,
|
||||
"image_path": content.image_path
|
||||
}
|
||||
for section, content in generator.section_contents.items()
|
||||
}
|
||||
}, indent=2)
|
||||
st.markdown('<div class="outline-content">', unsafe_allow_html=True)
|
||||
st.code(json_output, language="json")
|
||||
st.download_button(
|
||||
"Download JSON",
|
||||
json_output,
|
||||
file_name="blog_outline.json",
|
||||
mime="application/json"
|
||||
)
|
||||
st.markdown('</div>', unsafe_allow_html=True)
|
||||
|
||||
elif output_format == "HTML":
|
||||
html_output = f"""
|
||||
<!DOCTYPE html>
|
||||
<html>
|
||||
<head>
|
||||
<title>{topic} - Blog Outline</title>
|
||||
<style>
|
||||
body {{ font-family: Arial, sans-serif; max-width: 100%; margin: 0 auto; padding: 20px; }}
|
||||
.section {{ margin-bottom: 30px; }}
|
||||
.content {{ background: #f8f9fa; padding: 15px; border-radius: 4px; }}
|
||||
img {{ max-width: 100%; height: auto; }}
|
||||
</style>
|
||||
</head>
|
||||
<body>
|
||||
<h1>{topic}</h1>
|
||||
{generator.to_markdown().replace('#', '##')}
|
||||
</body>
|
||||
</html>
|
||||
"""
|
||||
st.markdown('<div class="outline-content">', unsafe_allow_html=True)
|
||||
st.code(html_output, language="html")
|
||||
st.download_button(
|
||||
"Download HTML",
|
||||
html_output,
|
||||
file_name="blog_outline.html",
|
||||
mime="text/html"
|
||||
)
|
||||
st.markdown('</div>', unsafe_allow_html=True)
|
||||
|
||||
except Exception as e:
|
||||
st.error(f"Error generating outline: {str(e)}")
|
||||
st.markdown('</div>', unsafe_allow_html=True)
|
||||
|
||||
# Display the outline if it exists in session state
|
||||
if st.session_state.outline:
|
||||
st.markdown('<div class="preview-section">', unsafe_allow_html=True)
|
||||
for section, subsections in st.session_state.outline.items():
|
||||
content = st.session_state.section_contents.get(section)
|
||||
display_section(section, subsections, content, generator)
|
||||
st.markdown('</div>', unsafe_allow_html=True)
|
||||
|
||||
st.markdown('</div>', unsafe_allow_html=True) # Close the outline container
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
Reference in New Issue
Block a user